Particle Swarm Optimization and Real-Road/Driving-Cycle Analysis Based Powertrain System Design for Dual Motor Coupling Electric Vehicle

Abstract

In this study, a planetary gear based dual motor coupling electric vehicle is proposed, which achieves higher system efficiency by enabling motor working under high operating efficiency area. Firstly, the dynamic characteristics of the proposed configuration are analyzed and the reasonable working modes are established. Secondly, the optimal dual motor parameters are derived according to the statistical analysis on the typical driving conditions and the collected real road driving data. Especially, the optimal parameters of planetary gear and final transmission ratio are obtained using particle swarm optimization algorithm. Finally, based on the developed mode shift algorithm, the dual motor coupling full vehicle model is developed and the vehicle performance is analyzed using MATLAB/Simulink. For the UDDS (Urban Dynamometer Driving Schedule) driving cycle, it is seen from the simulation results of motor operating points that the proposed dual motor configuration is mostly operated under the high efficiency range, and the power consumption is significantly reduced by 7.6% compared with the single motor configuration. For the NEDC (New European Driving Cycle), WLTC (Worldwide Harmonized Light Vehicles Test Cycle) and real road driving conditions, the proposed dual motor configuration also achieves system efficiency improvement of 5.0%~16.3%, which confirms the validity of the proposed configuration and its corresponding parameter matching and control algorithm development.